This application is in response to a Request for Applications (RFA): DK-03-010, Basic Research in Interstitial Cystitis. Diagnosis of interstitial cystitis (IC) is primarily based on symptoms, as there are no currently available blood or urine tests due to the lack of demonstrated biological markers. In addition, there are currently no consistently effective treatments for IC, and a precise etiology has not been demonstrated. Thus, one area of critical need is to identify disease markers for IC. Markers that can be used in sensitive, specific tests/screens for IC may have immense value in the accurate diagnosis of disease, as well as elucidating potential pathobiological pathways that may translate into a mode of action for the treatment of IC. The identification of disease signatures is one of the research areas of special interest, and anticipated goals of this RFA. Therefore, to fulfill this goal, we will: 1) generate disease-associated urinary protein profiles of clinically annotated interstitial cystitis specimens with surface enhanced laser desorption ionization time-of-flight (SELDI-TOF) mass spectrometry; 2) characterize potential disease-associated proteins, based on results obtained from SELDI-TOF, by 2-0 difference gel electrophoresis (2-D QIGE) and tandem mass spectrometry (msims)-based sequence identification; 3) compare relative expression levels of low- abundance urinary proteins in clinically annotated IC specimens with isotope-coded affinity tag (ICAT) and mass spectrometry; 4) mine proteomics data and to create predictive bioinformatics models (i.e., hierarchical cluster analysis and K-means methods, canonical correlations, discriminant analysis, Bayesian statistics, self-organizing maps and neural networks) that can stratify samples according to clinical information and/or outcome; 5) develop a biorepository consisting of urine, serum, and plasma specimens as a resource for future assays, including the creation of resources in the form of frozen urine, serum, and plasma protein arrays, as well as resources for global metabolomics studies. Through these specific aims, our goal is to fulfill the need to develop reliable predictive and diagnostic tools for IC, which is deemed to be a high-priority by the NIDDK Bladder Research Progress Group.